unique color per class

app.py

@@ -82,7 +82,8 @@ def streaming_object_detection(recording_id: str, img):
     # convert outputs (bounding boxes and class logits) to COCO API
     # let's only keep detections with score > 0.9
 
-    target_sizes = torch.tensor([img.size[::-1]])
+    height, width = img.shape[:2]
+    target_sizes = torch.tensor([[height, width]])  # [height, width] order
     results = processor.post_process_object_detection(
         outputs, target_sizes=target_sizes, threshold=0.9
     )[0]
@@ -94,6 +95,14 @@ def streaming_object_detection(recording_id: str, img):
             array=results["boxes"],
             array_format=rr.Box2DFormat.XYXY,
             labels=[model.config.id2label[label.item()] for label in results["labels"]],
+            colors=[
+                (
+                    label.item() * 50 % 255,
+                    (label.item() * 80 + 40) % 255,
+                    (label.item() * 120 + 100) % 255,
+                )
+                for label in results["labels"]
+            ],
         ),
     )